Create app

app.py

@@ -0,0 +1,91 @@
+from openai import OpenAI
+from gtts import gTTS
+from io import BytesIO,StringIO
+#Using streamlit app framework
+import streamlit as st
+
+
+
+
+#Creating client
+client= OpenAI(
+    api_key="sk-1234567890",
+    base_url='http://localhost:8000/v1'
+)
+
+
+# Title of the app
+st.title("TherapyBot- A Chatbot for Mental Health Support")
+
+
+
+
+#Uploading medical records
+uploaded_file = st.file_uploader("", type=["txt"], label_visibility="collapsed")
+css = '''
+<style>
+    [data-testid='stFileUploader'] {
+        width: max-content;
+    }
+    [data-testid='stFileUploader'] section {
+        padding: 0;
+        float: left;
+    }
+    [data-testid='stFileUploader'] section > input + div {
+        display: none;
+    }
+    [data-testid='stFileUploader'] section + div {
+        float: right;
+        padding-top: 0;
+    }
+
+</style>
+'''
+st.markdown(css, unsafe_allow_html=True)
+
+doc_data = ""
+#If user uploads a file
+if uploaded_file is not None:
+
+    # To read file as string:
+    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
+    doc_data = stringio.read()
+    doc_data = "This is my medical record - "+doc_data+" Please answer the following question based on the earlier medical record- "
+    
+
+
+#Taking user input
+prompt= st.chat_input('Chat to start or upload any medical records. How can I help?')
+
+
+#If users types prompt and hits enter
+if prompt:
+    st.chat_message("user").markdown(prompt)
+    #Chat Completion
+    reponse= client.chat.completions.create(
+        #which model we wanna use
+        model='D:\CHATBOT_PROJ_NEW\MentaLLaMA-chat-7b-GGUF-q8\MentaLLaMA-chat-7b-GGUF-q8.gguf',
+        #pass through the prompt
+        messages=[{
+            'role': 'user',
+            'content': doc_data+prompt
+        }],
+        #Add streaming
+        stream=True
+    )
+    with st.chat_message("ai"):
+        completed_message = ""
+        message= st.empty()
+        #Streaming the response out
+        for chunk in reponse:
+            if chunk.choices[0].delta.content is not None:
+                #print(chunk.choices[0].delta.content, flush=True, end="")
+                completed_message += chunk.choices[0].delta.content
+                message.markdown(completed_message)
+        
+        sound_file = BytesIO()
+        tts = gTTS(completed_message, lang='en')
+        tts.write_to_fp(sound_file)
+        st.audio(sound_file)
+
+